This material is based upon work supported by NASA through contract NNL16AA05C and cooperative agreement NNX14AB60A. Any mention of a commercial product, service or activity in this material does not constitute NASA endorsement. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration and partner organizations.

AbstractAlthough Cladophora is naturally occurring and nontoxic, the accumulation and decay of thisgreen macroalgae creates salient socioeconomic issues for communities situated along theshoreline of Lake Michigan. When Cladophora washes ashore and decays, it createsunaesthetic and unpleasant smelling beaches, potentially endangering public health andthreatening the local tourism economy. Furthermore, decaying Cladophora promotes thegrowth of toxic bacteria, which can impact organisms that come into contact with it. Incollaboration with Groundwork Milwaukee, the 2018 NASA DEVELOP Lake MichiganWater Resources team created Cladophora Habitat Suitability and Washup Predictive Maps toidentify areas where the algae grows and predict where it will most likely come ashore. Thesemaps were created using Landsat 8 Operational Land Imager (OLI) and Aqua ModerateResolution Imaging Spectroradiometer (MODIS) imagery of Lake Michigan near Milwaukee,WI, from June to September for the years 2016 and 2017. The results of this project will bevalidated during the fall 2018 DEVELOP term using in situ data of Cladophora sightingscollected by Groundwork Milwaukee using an ArcGIS Collector App. To encouragecommunity involvement, the team developed a project story map and provided GroundworkMilwaukee with content for their community science social media campaign that highlightsthe significance of this project while informing members of the general public about howthey can contribute to cleanup efforts. These products will allow local organizations such asGroundwork Milwaukee to identify, monitor, and predict the movement of Cladophora andallocate cleanup resources more efficiently along the shores of Lake Michigan.

Methodology & Results

Project Partner

California – Ames | Summer 2018Lake Michigan Water Resources

Utilizing NASA Earth Observations and Community Science to Detect and Map the Displacement of Cladophora along the Milwaukee County Shoreline

Conclusions Cladophora Habitat Suitability Maps show more favorable habitat to the north outside of the

Milwaukee County boundary, suggesting that Cladophora is carried down south by water surfacecurrents before being deposited on beaches.

SAV maps show a substantial amount of Cladophora within the 10-meter bathymetry contour.

Cladophora Predictive Washup Maps suggest that the southern beaches will generally experiencemore algae deposition.

All FAI images had an approximate average value of zero, indicating there is no floating algae inthe study area or that floating mats of Cladophora are too small to be detected in Landsat-sizedpixels.

In situ data, gathered by Groundwork Milwaukee via Collector for ArcGIS, will be used duringthe fall 2018 DEVELOP term to assess the accuracy of the Cladophora Predictive Washup Map.

Studying the growth and deposition of Cladophora in Milwaukee County is difficult due to the lackof relevant data and field research being performed in our study area.

Objectives

AcknowledgementsLawrence Hoffman (GIS Program Manager, Groundwork Milwaukee)

Deneine Powell (Executive Director, Groundwork Milwaukee)

Alex Halloway (GIS Intern, Groundwork Milwaukee)

Alex Litscher (GIS Intern, Groundwork Milwaukee)

Dr. Juan Torres-Pérez (Bay Area Environmental Research Institute, NASA Ames Research Center)

Dr. Sherry Palacios (Bay Area Environmental Research Institute, NASA Ames Research Center)

Jenna Williams (DEVELOP Center Lead, NASA Ames Research Center)

John Dilger (DEVELOP Geoinformatics Fellow, NASA Ames Research Center)

Create Cladophora Habitat Suitability and WashupPredictive Maps to identify factors influencing growth, displacement, and deposition

Utilize the ArcGIS Collector tool via a mobile phone application to gather in situ data of Cladophora washuplocations

Produce a project story map and social media campaign content to inform the public about how they can help address issues regarding Cladophoranuisances in their own communities Landsat 8 OLI Aqua MODIS

Groundwork USA, Groundwork Milwaukee

Team Members

Jerrold Acdan

Project Lead

Lawrence Fujiwara Ella Golovey

Doctors Park

South Shore Park

Atwater Beach

Bradford Beach

McKinley BeachVeterans Lagoon

Grant Park Beach

Milwaukee

South

Milwaukee

L a ke M i c h i g a n

Beach

River

Milwaukee County

County Boundary

WI

IAIL

IN

MI

OH

!( Beach

24k_Hydro_Flowlines_RiversStreams

Milwaukee County

County Boundary

±

Earth Observations

Study Area

Steven Chao

AQUA MODIS

Landsat 8 OLI

EARTH OBSERVATIONS

Cladophora Habitat

Suitability Map

END PRODUCT

Submerged Aquatic Vegetation Map

DERIVED ANCILLARY DATA

Bathymetry

Mussel Distribution

Substrate

ACQUIRED SUITABILITY DATA

Turbidity

Water Temperature

DERIVED SUITABILITY DATA

Data Processing

Submerged Aquatic Vegetation Mapping Algorithm (SAVMA)

Compare

Habitat Suitability

Low

High

Submerged Aquatic Vegetation Map

Sand

Less Dense SAV

Dense SAV

Cladophora Habitat Suitability Map

Milwaukee Milwaukee

B

C

D

E

A Doctors Park

AtwaterBeach

McKinley Beach

BradfordBeach

South ShorePark

GrantPark

Beach

A

B

C

D

E

Population Density

Low HighBeach

CladophoraWashup Predictive Map

Milwaukee

South

Milwaukee

0 10

Kilometers 0 10

Kilometers

Predictive Value

HighLow

Multi-Criteria

Evaluation

Milwaukee

Floating Algae Index (FAI) Map

High

Low

0 1

Kilometer

Bradford

Beach

McKinley

Beach

FAI Value

N

0 10

Kilometers

NN

Cladophora Washup

Predictive Map

END PRODUCT

ArcGIS Collector

in situ Data

END PRODUCT

Ground Truth

Floating Algae Index Map

DERIVED ANCILLARY DATA

Landsat 8 OLI

EARTH OBSERVATIONSData

Processing

Population Density

Water Current Direction

ACQUIRED PREDICTIVE FACTORS

Multi-Criteria

EvaluationCompare

Shoreline Curvature

Nearshore Structures

DERIVED PREDICTIVE FACTORS

SAVMA Classification

N